https://github.com/python/cpython/commit/fefd5d97111364afa027ae580c3244f427dda59d
commit: fefd5d97111364afa027ae580c3244f427dda59d
branch: main
author: Mariusz Felisiak <felisiak.mariusz@gmail.com>
committer: JelleZijlstra <jelle.zijlstra@gmail.com>
date: 2024-04-18T22:36:24-07:00
summary:
gh-64588: Clarify the difference between mu and xbar in statistics docs (#117333)
Thanks Davin Potts for the clarification idea.
files:
M Doc/library/statistics.rst
diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst
index 873ccd650f45cd..cc72396964342e 100644
--- a/Doc/library/statistics.rst
+++ b/Doc/library/statistics.rst
@@ -501,9 +501,9 @@ However, for reading convenience, most of the examples show sorted sequences.
variance indicates that the data is spread out; a small variance indicates
it is clustered closely around the mean.
- If the optional second argument *mu* is given, it is typically the mean of
- the *data*. It can also be used to compute the second moment around a
- point that is not the mean. If it is missing or ``None`` (the default),
+ If the optional second argument *mu* is given, it should be the *population*
+ mean of the *data*. It can also be used to compute the second moment around
+ a point that is not the mean. If it is missing or ``None`` (the default),
the arithmetic mean is automatically calculated.
Use this function to calculate the variance from the entire population. To
@@ -573,8 +573,8 @@ However, for reading convenience, most of the examples show sorted sequences.
the data is spread out; a small variance indicates it is clustered closely
around the mean.
- If the optional second argument *xbar* is given, it should be the mean of
- *data*. If it is missing or ``None`` (the default), the mean is
+ If the optional second argument *xbar* is given, it should be the *sample*
+ mean of *data*. If it is missing or ``None`` (the default), the mean is
automatically calculated.
Use this function when your data is a sample from a population. To calculate
@@ -590,8 +590,8 @@ However, for reading convenience, most of the examples show sorted sequences.
>>> variance(data)
1.3720238095238095
- If you have already calculated the mean of your data, you can pass it as the
- optional second argument *xbar* to avoid recalculation:
+ If you have already calculated the sample mean of your data, you can pass it
+ as the optional second argument *xbar* to avoid recalculation:
.. doctest::
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commit: fefd5d97111364afa027ae580c3244f427dda59d
branch: main
author: Mariusz Felisiak <felisiak.mariusz@gmail.com>
committer: JelleZijlstra <jelle.zijlstra@gmail.com>
date: 2024-04-18T22:36:24-07:00
summary:
gh-64588: Clarify the difference between mu and xbar in statistics docs (#117333)
Thanks Davin Potts for the clarification idea.
files:
M Doc/library/statistics.rst
diff --git a/Doc/library/statistics.rst b/Doc/library/statistics.rst
index 873ccd650f45cd..cc72396964342e 100644
--- a/Doc/library/statistics.rst
+++ b/Doc/library/statistics.rst
@@ -501,9 +501,9 @@ However, for reading convenience, most of the examples show sorted sequences.
variance indicates that the data is spread out; a small variance indicates
it is clustered closely around the mean.
- If the optional second argument *mu* is given, it is typically the mean of
- the *data*. It can also be used to compute the second moment around a
- point that is not the mean. If it is missing or ``None`` (the default),
+ If the optional second argument *mu* is given, it should be the *population*
+ mean of the *data*. It can also be used to compute the second moment around
+ a point that is not the mean. If it is missing or ``None`` (the default),
the arithmetic mean is automatically calculated.
Use this function to calculate the variance from the entire population. To
@@ -573,8 +573,8 @@ However, for reading convenience, most of the examples show sorted sequences.
the data is spread out; a small variance indicates it is clustered closely
around the mean.
- If the optional second argument *xbar* is given, it should be the mean of
- *data*. If it is missing or ``None`` (the default), the mean is
+ If the optional second argument *xbar* is given, it should be the *sample*
+ mean of *data*. If it is missing or ``None`` (the default), the mean is
automatically calculated.
Use this function when your data is a sample from a population. To calculate
@@ -590,8 +590,8 @@ However, for reading convenience, most of the examples show sorted sequences.
>>> variance(data)
1.3720238095238095
- If you have already calculated the mean of your data, you can pass it as the
- optional second argument *xbar* to avoid recalculation:
+ If you have already calculated the sample mean of your data, you can pass it
+ as the optional second argument *xbar* to avoid recalculation:
.. doctest::
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